Gas Phase Combustion—Flamelet Models

To reduce computational expense in combustion simulations, Simcenter STAR-CCM+ can precompute reactions for representative scenarios and tabulate the relevant quantities. A turbulent flame can be approximated as an ensemble of laminar flamelets.

The term flamelet is used to describe a basic 0D or 1D laminar flame geometry. When flamelets are calculated, the detailed thermo-chemistry of the temperature and species within the flame is parameterized by two or more variables.

Each flamelet model in Simcenter STAR-CCM+ makes a different assumption about the composition of the flamelets:
  • The Chemical Equilibrium (CE) model assumes that the turbulent flow is in chemical equilibrium, hence chemistry is very fast compared to flow and mixing. This corresponds to the zero strain of the Steady Laminar Flamelet (SLF) model, or the burnt state of the Flamelet Generated Manifold (FGM) model. The thermo-chemical state is parameterized by mixture fraction Z and enthalpy h .
  • The SLF model embeds steady diffusion flamelets in the turbulent flow. The assumption is that chemistry is fast compared to flow and mixing, and hence the flame is thin. The thermo-chemical state is parameterized by mixture fraction Z , and the scalar dissipation rate χ .
  • The FGM model assumes that the thermo-chemical states in a turbulent flame are similar to those in a laminar flame. The thermo-chemical state is parameterized by mixture fraction Z , reaction progress c , and enthalpy h . Since there is only one reacting variable (reaction progress, c ), only one chemical time scale of the heat release reactions is represented.

The CE model and the SLF model are limited to modeling fast chemistry without ignition and extinction, however, the FGM model can be used in any combustor.

For premixed and partially-premixed systems, there are flame fronts which move at a turbulent flame speed. Therefore, for the flamelet models that cannot capture the flame front, Simcenter STAR-CCM+ provides additional flame propogation models.